LENOVO 90D7A00600
Geekbench AI Score
303
Single Precision Score
300
Half Precision Score
531
Quantized Score
Geekbench AI 1.3.0 for Windows x86 (64-bit)
Result Information
| User | kitsunechan_2525 |
| Upload Date | June 04 2025 12:48 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Pentium(R) CPU G3250 @ 3.20GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 IoT LTSC (64-bit) |
| Model | LENOVO 90D7A00600 |
| Motherboard | LENOVO 3098 |
| CPU Information | |
|---|---|
| Name | Intel Pentium G3250 |
| Topology | 1 Processor, 2 Cores |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
193
35.9 IPS |
|
|
Image Classification (HP)
|
100% |
192
35.8 IPS |
|
|
Image Classification (Q)
|
100% |
353
65.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
237
3.84 IPS |
|
|
Image Segmentation (HP)
|
100% |
236
3.83 IPS |
|
|
Image Segmentation (Q)
|
99% |
404
6.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
334
0.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
331
0.39 IPS |
|
|
Pose Estimation (Q)
|
94% |
701
0.82 IPS |
|
|
Object Detection (SP)
|
100% |
183
14.5 IPS |
|
|
Object Detection (HP)
|
100% |
183
14.5 IPS |
|
|
Object Detection (Q)
|
87% |
360
28.9 IPS |
|
|
Face Detection (SP)
|
100% |
526
6.25 IPS |
|
|
Face Detection (HP)
|
100% |
532
6.32 IPS |
|
|
Face Detection (Q)
|
97% |
942
11.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
466
3.59 IPS |
|
|
Depth Estimation (HP)
|
99% |
464
3.57 IPS |
|
|
Depth Estimation (Q)
|
81% |
855
6.76 IPS |
|
|
Style Transfer (SP)
|
100% |
814
1.05 IPS |
|
|
Style Transfer (HP)
|
100% |
823
1.06 IPS |
|
|
Style Transfer (Q)
|
98% |
2094
2.70 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
205
7.57 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
205
7.58 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
428
15.9 IPS |
|
|
Text Classification (SP)
|
100% |
246
328.9 IPS |
|
|
Text Classification (HP)
|
100% |
246
328.0 IPS |
|
|
Text Classification (Q)
|
91% |
295
396.7 IPS |
|
|
Machine Translation (SP)
|
100% |
234
4.04 IPS |
|
|
Machine Translation (HP)
|
100% |
213
3.67 IPS |
|
|
Machine Translation (Q)
|
100% |
234
4.03 IPS |
